Mesh quality after snappyHex
i'm running the case of a flow inside a rough channel. I'm trying to generate a proper mesh. The bottom roughness is formed by small cubical blocks.
Each block's surface mesh should be formed by approximately 4 cells in the vertical direction and 2 cells in the two horizontal directions (although the refined cells should be about 2.5 units wide, while the blocks are 4.5 units wide, so a BIT LESS than 2 cells).
After snappyHex, however, i ran checkMesh and the result is the following
Boundary definition OK.
Cell to face addressing OK.
Point usage OK.
Upper triangular ordering OK.
Face vertices OK.
Number of regions: 1 (OK).
Checking patch topology for multiply connected surfaces ...
Patch Faces Points Surface topology
in 6410 6743 ok (non-closed singly connected)
out 5600 5781 ok (non-closed singly connected)
left 18367 19132 ok (non-closed singly connected)
right 18367 19132 ok (non-closed singly connected)
top 56000 56541 ok (non-closed singly connected)
bottom 510205 595645 ok (non-closed singly connected)
spires_patch0 46711 48691 ok (non-closed singly connected)
roughness_patch0 603177 690348 ok (non-closed singly connected)
hangar_patch0 38240 38481 ok (non-closed singly connected)
Overall domain bounding box (-10 -7 -0.00139171) (30 7 4)
Mesh (non-empty, non-wedge) directions (1 1 1)
Mesh (non-empty) directions (1 1 1)
Boundary openness (3.74041e-16 1.31646e-15 -1.22914e-13) OK.
Max cell openness = 4.21681e-16 OK.
Max aspect ratio = 5.83191 OK.
Minumum face area = 1.76458e-05. Maximum face area = 0.0200125. Face area magnitudes OK.
Min volume = 6.93409e-07. Max volume = 0.00200123. Total volume = 2237.84. Cell volumes OK.
Mesh non-orthogonality Max: 57.4584 average: 12.2611
Non-orthogonality check OK.
***Error in face pyramids: 7 faces are incorrectly oriented.
<<Writing 7 faces with incorrect orientation to set wrongOrientedFaces
***Max skewness = 7.12497, 102 highly skew faces detected which may impair the quality of the results
<<Writing 102 skew faces to set skewFaces
Coupled point location match (average 0) OK.
How can i improve the result?
I don't know if these informations are enough. If you need to know more i can post some screenshots or others dicts.
Thank you very much